Spatial-Temporal Changes of Soil Organic Carbon Content in Wafangdian, China

Shuai Wang, Qiubing Wang, Kabindra Adhikari, Shuhai Jia, Xinxin Jin and Hongbin Liu
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Shuai Wang: College of Land and Environment, Shenyang Agricultural University, Shenyang 110866, Liaoning Province, China
Qiubing Wang: College of Land and Environment, Shenyang Agricultural University, Shenyang 110866, Liaoning Province, China
Kabindra Adhikari: Department of Soil Science, University of Wisconsin-Madison, Madison, WI 53706, USA
Shuhai Jia: College of Land and Environment, Shenyang Agricultural University, Shenyang 110866, Liaoning Province, China
Xinxin Jin: College of Land and Environment, Shenyang Agricultural University, Shenyang 110866, Liaoning Province, China
Hongbin Liu: College of Land and Environment, Shenyang Agricultural University, Shenyang 110866, Liaoning Province, China

Sustainability, 2016, vol. 8, issue 11, 1-16

Abstract: Soil organic carbon (SOC) plays an important role in soil fertility and the global carbon cycle. A better understanding of spatial-temporal changes of SOC content is essential for soil resource management, emission studies, and carbon accounting. In this study, we used a boosted regression trees (BRT) model to map distributions of SOC content in the topsoil (0–20 cm) and evaluated its temporal dynamics from 1990–2010 in Wafangdian City, northeast of China. A set of 110 (1990) and 127 (2010) soil samples were collected and nine environment variables (including topography and vegetation) were used. A 10-fold cross-validation was used to evaluate model performance as well as predictive uncertainty. Accuracy assessments showed that R 2 of 0.53 and RMSE (Root-mean-square error) of 9.7 g∙kg −1 for 1990, and 0.55, and 5.2 g∙kg −1 for 2010. Elevation and NDVI (Normalized Difference Vegetation Index) were the two important variables affecting SOC distribution. Results showed that mean SOC content decreased from 19 ± 14 to 18 ± 8 g∙kg −1 over a 20 year period. The maps of SOC represented a decreasing trend from south to north across the study area in both periods. Rapid urbanization and land-use changes were accountable for declining SOC levels. We believe predicted maps of SOC can help local land managers and government agencies to evaluate soil quality and assess carbon sequestration potential and carbon credits.

Keywords: soil organic carbon; digital soil mapping; boosted regression trees; land-use change; topography (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2016
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (7)

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